{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 《零基础学Python》实操练习题\n",
    "\n",
    "## 《条件与循环语句》"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**作业说明:**  为了帮助同学们掌握、巩固课程学习内容，并主动结合知识点思考问题逻辑，从而形成编程思维，我们为大家设计了2个不同难度的作业~\n",
    "\n",
    "▶基础题：针对当前章节传授知识点设计的题目，用于考察大家的学习掌握情况，同学们一定要尝试做出来哟~\n",
    "\n",
    "▶思考题：针对当前或近期所学内容设计的题目，用于将多个知识点串联、或是引发对后续学习内容的提前思考。同学们可能无法正确解答，但这些内容都是老师精心设计哒，目的是引发大家对知识点的深入探究~我们会有提示引导同学们思考的方向，相信这些思考会让大家不断提高自主探索的能力。\n",
    "\n",
    "★针对此章节的题目，老师在每一部分都给出了思维导图帮助大家梳理逻辑，建议同学们读完题目后先自己思考一遍呦！\n",
    "★对于以上说明和作业问题，同学们可以在群里积极参与讨论或向助教老师咨询呦，相信大家只要认真完成作业，一定能够收获满满！"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.【基础题】分支语句\n",
    "\n",
    "学校的期末考试中，教务处要求对分数设置分层：≥90为优秀、80(含)\\~90(不含)为良好、60(含)~80(不含)为及格、小于60为不及格。\n",
    "<br>要求：结合if…elif…else语句，当学生输入成绩后即可显示分数和等级，即系统输出：同学，你此次的分数为#分，等级为#。\n",
    "\n",
    "注意：大家要看清变量的取值区间，思考一下进行数值的大小比较时是否需要加等号呦"
   ]
  },
  {
   "attachments": {
    "image-3.png": {
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u+VwwoDLd4q1EGjxye7z5yO1x4MF/iKeffjo2btwYL774Yuzbty+Ghobi7NmzMTExEZcuXYrr16/7q/X16f4uqRWwAoYhtwEUuHHjRjYAXrlyJS5evBgjIyNx8uTJOHToULamBAvCs88+mw2iWBWWL1+erTtZunRpeCuHBqwTou5Wr14dGzZsyNYLvfLKK3HgwIF466234ty5czE5OWkY8i3BCliB+ilgGKpfnTcqMTCEdejq1asxNTUVFy5cyKZNsBjs378/du7cmU2pbNq0KRtI161bly3A5Ykkb8XXgMXSrBFiagyoZeH0Sy+9FHv37s3WC506dSoDYECYdWO2DDXqJT5nBaxAZRUwDFW2audUsBSGmCZhuuT8+fOZdYjFtUyl7Nq1K3bs2BEvvPBCtvCWAZWNx7O9FVsD6onF0tu3b8+mxrAIAUJvvPFGZhViimxsbCxbPI11EDCmTRTxd1MRM+U8WQErUG4FDEPlrr9O5V4wdO3atWAwlHWIQfLEiRPZAtuDBw/G66+/ni245d00bACSt3JoQH2xWJo6ZGqMdwsdP348hoeHY3R0NJsiwyqEddAw1Kme5XisgBUohQKGoVJUU9czCQyxMT3CYIh1iPUjTJdhIeKFfEAR02bHjh3LplawGDGgeiuHBtQXT41Rh0AQU2PALiCEJXB6ejqre9qA2kPXG948ErBlaB6iOYgVsAKzK2AYml2fOl2VdSgFItaQ8O4ZBsy33347W2SLJYF30ngrnwbUHQBEXVKn1C11DPxiESzyWiH1RcOQlLBrBaxAxxQwDHVMykpElAcipk2wGDBgYj1g8GRtCRtWI2/l0oB6ow6pSyx/TIcKhJgiZXqsyFNkdDLDUCVuNS6EFSiWAoahYtVHv3Oj6RENilgKGCSZOsNyABwxeHorrwbUIRv1Sb1Sv6lFiDZQ5J9hqMi147xZgZIqYBgqacV1MduNgEhQJDBiEPVWTg2oQ22CIFmDig5CNHvDUBc7v6O2AnVVwDBU15pvXW5BkVxZi+y+M5VUBR1Ut2WAILVYw5CUsGsFrEDHFDAMdUzKykaUDpjef+epuyrpULaGaxgqW405v1agBAoYhkpQSc6iFbACMwoYhmak8I4VsAKdUsAw1CklHY8VsAK9UMAw1AuVnYYVqJkChqGaVbiLawVKroBhqOQV6OxbgSIqYBgqYq04T1bACjRTwDDUTBmftwJWYN4KGIbmLZ0DWgEr0AcFDEN9EN1JWoGqK2AYqnoNu3xWoFoKGIaqVZ8ujRUohAKGoUJUgzNhBaxAmwoYhtoUyt6sgBVoXwHDUPta2acVsAL9V8Aw1P86cA6sQOUUMAxVrkpdICtQaQUMQ5WuXhfOCvRHAcNQf3R3qlbACsxPAcPQ/HRzKCtgBWZRwDA0izi+ZAWsQOEUMAwVrkqcIStQfgUMQ+WvQ5fACtRJAcNQnWrbZbUCPVLAMNQjoZ2MFbACHVHAMNQRGR2JFbACqQKGoVQN71sBK1B0BQxDRa8h588KlFABw1AJK81ZtgI1VsAwVOPKd9GtQLcUMAx1S1nHawWsQDcUMAx1Q1XHaQVqroBhqOYNwMW3AiVTwDBUsgpzdq1AGRQwDJWhlpxHK2AFpIBhSErYtQJWoGMKGIY6JqUjsgJWoAcKGIZ6ILKTsAJ1U8AwVLcad3mtQLkVMAyVu/6ceytQSAUMQ4WsFmfKCliBJgoYhpoI49NWwArMXwHD0Py1c0grYAV6r4BhqPeaO0UrUHkFDEOVr2IX0ApUSgHDUKWq04WxAsVQwDBUjHooYi5u3LgR6fbzn/88vFVDg7Re2S/TzzBUptpyXq1ASRQwDJWkonqcTQ2Wgp/r16+Ht+pooHrFVV2XBYoMQz2+GTg5K1AHBQxDdajluZWRQZFBUvBz7dq1uHr1aly5ciUuX748s126dCm8lUODtN7Ypy6pUzbql7pOwWhuLaa3vg1DvdXbqVmBWihgGKpFNbddSEBoasN3Y2rt3XGRbXBxTGpbc1dMrrkrJryVWoPxwXvi4sWLMT09ncGswCgForYbTB88Gob6ILqTtAJVV8AwVPUabr98sggBQtdO7fdWUQ3GVy+KkZGRuHDhQkxMTMTU1FRm7cNKVAYgMgy136ft0wpYgTYVMAy1KVTFvQFCbAyGWIQMQ9WFwdGV34yTJ0/GmTNn4vz58xkUTU5OZlYiAZHaQxGbvWGoiLXiPFmBkitgGCp5BXYo+7IKZTA0uNgwVFGrEJB7fuCOOHToUAwNDWVQdO7cuQyImDpjyow1RFo/1KHm1dFoDEMdldORWQErgAKGIbcDFBAMMRCyTsiWoepahoaXfi12794d+/fvjyNHjsSJEycyC9H4+PiMdcgw5PuCFbACtVLAMFSr6m5aWMEQ0yQsmDYMVReGTj3x5di+fXvs3Lkz9u3bF0ePHo3Tp0/H6OjozPqhIq8dsmWoaTf2BStgBeargGFovspVK5xgiGkSnhgzDFUXhk489sXYuHFjbNu2LXbt2hUHDx6csQ6xdohH7w1D1erfLo0VsAItFDAMtRCoJpf1XiEGQsNQdUEIyD3+6OdjzZo1sWnTptixY0dmHWL90NmzZ7Ony3h3lGGoJh3fxbQCVuAdBQxDbgkokMIQ7xGyZai6QPTmks/FqlWrYsOGDdl02d69e7OpsuHh4WDdEO8fKvIiak+T+Z5lBaxAxxUwDHVc0lJGaBiqLvzkwXbokdtjYGAg1q1bF1u3bo09e/ZkC6l51N4wVMru60xbASuwUAUMQwtVsBrhDUM1gqGHb4vly5fH4OBgbNmyJXuyjKfKWEQ9NjZmy1A1urRLYQWswFwUMAzNRa3q+hUMsV7E02TVBqNjD98Wy5Yty9YNbd68OYOhw4cPG4aq271dMitgBVopYBhqpVA9rhuGqg1A6VQZMLR06dIZGOKJMsNQPfq5S2kFrEATBQxDTYSp2WnDkGHI02Q16/QurhWwAu8pYBh6T4s67/UThob3be/402uHXlgfz69Ykm2pVWQ++68+M9B2/khzPmn0MowtQ3Xu6S67FbACDRUwDDWUpXYn+wVDj953V/zqr/xy3LfoKxlEAEaCmFauAIIwH//YR+PTn/zEDIh85Ld/I2666ab4pV/8hZlz8t+uS3zEwfbUkvvbikf+KZfSAczu/MJnZ93ktxeuYah23dsFtgJWoJUChqFWCtXjer9gCIgRtGCBAYAEFK1cgQOgIr8CIsEQrvzN5gIveWBJYYh48tdT4CFuoEz5SC1E7ZRptrx1+pphqB592qW0AlZgDgr0A4ZuvvnmmUHj8ccfn8ntokWLZs6zn/7wx0CT+ue64uL7SukPv7feemt6quV+mn4alrg1yJFe/se1W265ZcaP/DZy82FVrjQ9/Cgv+XLlw3fquF8wBEBgvUGrD//6rwVABHho45x01Dm5KSTc/nefmomDOPFDONzUX7N9+Vda7biKm/QAHqxbCsdxuuE3v8kvbrN8deO8YahTvcbxWAErUBkFeg1DGuQRMN3n5W/p4MA+5/gJRnQs8QUggAT+01+zMKmfdF9QkuZB6Qm4dC0FF/KQHitOlYcyNvvJj/Kf98t54l/o7/qZg3Hj0sSs0fQLhhjsgQimyoAHppQ4xgrDNc5Jd4EB1iT8ACGpRQeoAooIS3yEw81bdHScWnYEQ8BXCjGN9mUxEgyleVReU5fryrtcwRv+2Nf5XriGoVm7gi9aAStQRwV6DUMM8LKuCEDQXUAAxAgSBAd5KBDoAArExXWFF8AoznZhIgUzwirefF44r/zrGvnJ/0iXgS7NT+pH+ZWruNL8qpzN4kjjm21/etMDMfqN3wrcZlDUTxgCAAAbXAAF3bTWJwUNrmtKjOupBSiFj3b3BTPEKxiaDZ4EUfKr8GkeG6WdhyGVEb+a1iMPvdoMQ7P1Fl+zAlaglgr0GoYQGZjQoKFpL4GNKoHrgIL8p2DENQGIYCINJ1hJYUvXm7nyq3wpfZ0XkKTpkSellcYrsGl0TYCjsulY5ROUSRfi0LU0jbnsA0EjX/pQtjWDon7AkOBCrmBA02ZAQwoaXNcaI0EEVhWgJL+pHoGb/DXFT7pKEz8K065LGIXHVRzEi4VL8aR+mAbUeaxQ6bVe7RuG5tJ77NcKWIFaKNBrGEoHewZ6BgZ+s8EQfgQH+BVAaFBJXUEL/gQlAicd4599thRYZM0BVDiPOxsMcT215GQFycEe5W3kh7BpvrWf98sxfhfyS2GoGRT1A4ZUZrmCAU1DAT4pDKWAwb78593UXzoVJn8ptOTPzWeaTHEIsshzmm9dx03Ps59e69W+YWghvclhrYAVqKQCvYYhQQZiCmoADsEB5wQtsogwWKYwlK8IxZOHBsUjGOJ6GmezeAVA+FUcCkf+BVDEl4cXlUMDvFyFyeddxwqnvOp8t2AoD0XXp8bi+vXr0cvPcWBBEfigk2AASOA8U2IpPDAtpjDy28hNp6EUl6bh8D8bDM1nmow4UwDjWIupSUvpqS00cnsJRoYh9S67VsAKWIF3FRAMXVzx1WC/29vN/+f/MQMQgg6AQ/vpQCEwACQEI2Rb4JD61X4KHYpT8cxW6fhRHHLlX8dylRfcND3lC4ARROFqn/D8GqWluHHJt37ET7z8WAg9n/qZfOwzM9NkgqC8y/TZ1Mb7Y/rCuZ5+myyFHSAC2Em3FJbS8+w3AwiFwVKjp9FwBUQADzoTB2mytQMsaR2xTxiFF4Bp6kvTeZrGy4fNHzcri+LvpGsYUu+yawWsgBV4V4HpZ+5tOVDmB86FHDNlkw4EAguyI5jgegoEnE8tMPljVWYeTvLH8tfIzQNKClApzKT50Hn8al/51jEuP1xBktLStTQ/+bKnx42muxZSF43Cji7+g5gY+OrMIN/JQbhRXHkYSttGq/0UZhR3aqEBitI1OsARQKR40xcpCobSaTJNexEP+Uw3YCdNXwAGaJGmwpIGxworixF5YF/nBWoqRzddw1Da47xvBayAFYgILEIMiuMP/c28rA5ztVRg3ZjrT2AhQEmhSQOb3NRSwznByVzTbNc/6aVAp3DKcyPgEQwpz3lXec7DnC1D77caARJ5aJBFBk11XVYbrR+S3rpOHIKh1NoD7MgvQIM/XPkVXHEemJEVSmG4ns8faep6mn7eXzePDUPqpXatgBWwAu8qIBjCLfJPACQgapVXrDApGLXyP9/rgp48EOl8IxhqJy2FFxi1E6aZn9ksSnq6rB9rhhjwUzgANDTNJBhIr+tcM1fQA2wARam/dMF1IxgR4KQwRHidB2xS0CIOrgmS8JsHIqxFaR7YT8tjGGrWYmc///43is3u11etgBWwAm0pUBYYaqsw9tRQgUYwJAjSe4f68TRZHg4EKSlApPCQns/vpyAEuKTwk/pN40tBRtCDS1jiA2YAoLzFh6mwRiBDOK1HUlnSqTTykabfKI40r93at2WoYTfxSStgBeqsgGGo+rWfwlAeglT6osAQ8JGun0nhoRkcpOtwgBCtBQJOgBE9lYabWncUH+kBUAKY1AWOuC5Y0jWgh8XRxMl18pnGkaaTAlEKbYYhtb65ubYMzU0v+7YCVqANBQxDbYhUci/AUDMIUtH6BUMCGUACUBCgyG0FQ1q4LEjJx6HzeRe4URpYiPLXOcYiRP7kj7jzlh9N6wmE0nKQN64DZfn48ad4e+3aMqRWb9cKWAEr8K4ChqHqN4Uif5tMVpd0yiqFg1YwRHiAA7hoZGlpZNEBUgiXpoOVhzi4JmtPej3dB4pk+VG+cQElHcs/IMR+ClEpMMlfL13DUPX7vEtoBazAHBUwDM1RsIp675dlqBUEaAqqEegoLH7ycKNr7bqdiGO2tIAkyiA4ms1vt68ZhiraiV0sK2AF5q+AYWj+2lUpZFFhqNtgUMf4DUNV6rkuixWwAh1RwDDUERlLH4lhqHdfje83gBmGSt9dXQArYAU6rYBhqNOKljM+w5Bh6PTp0zE2NhbT09Nx7a0vmKEAACAASURBVNq1oE3cuHGjcA3aT5MVrkqcIStQfgUMQ+Wvw06UwDBkGDIMdaInOQ4rYAVKqYBhqJTV1vFMG4YMQ4ahjncrR2gFrEBZFDAMlaWmuptPw5BhyDDU3T7m2K2AFSiwAoahAldOD7NmGDIMGYZ62OGclBWwAsVSwDBUrProV24MQ4Yhw1C/ep/TtQJWoO8KGIb6XgWFyIBhyDBkGCpEV3QmrIAV6IcChqF+qF68NA1DhiHDUPH6pXNkBaxAjxQwDPVI6IInYxgyDBmGCt5JnT0rYAW6p4BhqHvalilmw1C9YGjZsmWxZs2a2Lx5c+zatSsOHz4chqEy9Vjn1QpYgY4qYBjqqJyljcwwVF8Y2r17t2GotD3XGbcCVqAjChiGOiJj6SMxDNUHhoYevi2wDA0ODmaWIcNQ6buvC2AFrMBCFTAMLVTBaoQXDF2+fDkm1twV/f6YqNPvHpwNPXJ7DAwMxNq1a2Pr1q2xZ8+eOHLkSJw5cybGx8f9bbJqdGmXwgpYgbkoYBiai1rV9WsY6h58FA3sgKEVK1bE+vXrY9u2bfHaa6/F0aNHDUPV7d4umRWwAq0UMAy1Uqge11MYGh+8J8ZXL4rRVXfG+YE7Ynjp1+L0E1+OE499MY4/+vl4c8nnggGV6RZvJdLgkdvjzUdujwMP/kO2eHrjxo2xY8eO2LdvXwwNDcXZs2djYmIiLl265K/W16Pbu5RWwApIAcOQlKi3e+PGjbh+/XpcuXIlLl68GCMjI3Hy5Mk4dOhQsKYEC8Kzzz4bTz/9dKxcuTKWL1+erTtZunRpeCuHBqwTou5Wr14dGzZsiC1btsQrr7wSBw4ciOPHj8e5c+dicnIygyHaAoBMuyja76aiZcj5sQJWoPwKCIYmV3w1u/Fx80u38pfQJWhHAeqcwe/q1asxNTUVFy5cyKZNsBjs378/du7cmQHRpk2bsoF03bp12QJcHs/2VnwNWCzNGiGmxoBaQOill16KvXv3ZuuFTp06lQEwIMy6McNQO73GfqyAFaiMAheXfSlGvvShmHjsf2U3QG6C165dm7kZFvW/w8pUQEEKksIQ0yRMl5w/fz6zDrG4lqkU3kfDtMoLL7yQLbxlQGXjXTXeiq0B9cRi6e3bt8eLL76YWYQAoTfeeCPeeuutbIpsbGwsWzyNdVD9nnZRtJ8tQ0WrEefHCpRYgesT52PyiX+M8e//eUw8+vcx/tBfxviPPh3Tw8cyMzkDIjfFFIyKeGMscRUUKuuCIeqbepd1iHUkJ06cyBbYHjx4MF5//fVswS1TZ2wAkrdyaEB9sViaOmRqjBctMj02PDwco6Oj2RQZViHagGCoUI303cwYhopYK86TFSiZAgx6U88/GGPf/lhMbX7wfY9QX3rx8Ri9+49idM09ceHtc5l1gEFRN8gim85LVg2Fyy7tgo06ZqoMGGb9CNNlWIh4OzFQxLTZsWPHsqkVLEYMqN7KoQH1xVNj1CHWIKbGgF1ACEvg9PR0Vve0AbWHwjXUiDAMFbFWnCcrUCIFrhx9OS58+2PBOqGrQzvfB0J6/PfqW3tictUdMXL3H8XZl56Ot99+O3v3CFAkS5H+a+SG6V91FKA+qdsUiFhDwrtnGDBpCyyyxZLAO2m8lU8D6g4AAnBZJM/UmBZN07/L8A+PYag69xyXxAr0VIF0SuzK/mcbQpBgSO7Vg8/HhR/8ZZz//l/F8KE92Y1Tj91iOSjDTbOnIlcksTwQYRXEYgAUUf+AEQMoG1Yjb+XSgHqjDqlLIIh/ctIp8TL8o2MYqsjNxsWwAr1SgIGt2ZSYoKeVy9TZyOI/jOEV34qzp09mg5+eOPF6ol7VZO/Soc0IiGQlop4BYCwHwBGDp7fyakAdslGf1Gu+H1P/Rf4ZhopcO86bFSiYAu1MibUCIV1n6mxi5T/F24v/MM68+FRmYue/S0+dFazSO5SdRkCEJZBBU2DEIOqtnBqoHlMIKoNFSM3bMCQl7FoBK9BUgflMiQl6WrlMnY3+219kU2dn3tjtqbOmtVCNC4IiuQyY3qqjgepVbllarWGoLDXlfFqBPijADW2hU2KtYEjXPXXWhwruY5IaLO2+/4WkVdGjj01rXkkbhuYlmwNZgeor0MkpMQFPK9dTZ9VvVy6hFSiiApWEoaqQda/KUcSG6Tz1T4FuTom1giFd99RZ/+rfKVuBOipQahhKYaHRnDOL87zNrkFet1TTOnaIOpeZuu/VlJigp5XrqbM6t0iX3Qr0ToHSwZAG68v7N8bUxvuzjdf9j//gr+LC4o9m30Pim0jePqjB6F2/H2P/9s7nESaf+ddgm9q7IS5PTc48wVHWJwF612WqmVI/psRagZCue+qsmm3OpbICRVKgNDD086uX49Jra2Ny2Rdj9I7fjIkffTourvqnbOO/x0s7lwWmdd1A7e7/gBbog07oJe3Gf/ipTM+xn3w2xl98MqZGz868LEvvipD1CBD1r1oKFGFKrN2+6qmzarU9l8YKFEmBwsMQEDS98b648K3fjYlH/mdMb7q/6Sv/272p2t/7QYn/vPmeFB/WHP3m78SFgTti/Nyp7O2w6VtE/XbgInXdheWliFNi7fZLT50trO4d2gpYgQ8qUGgYuvTqymzq6+JT3zAAnXo/wLQ7cMzVH2B0ce3dMbLoI3F+wwMxev7szMf2/A2pD3agMp4p8pRYu+3VU2dlbHnOsxUorgKFhKHroydj/F8/HpM/+UxcOfzCB6Z72r1h2t/8AYoPbk48+fnsw5rDr2+feREe3xMqy4f3itvt+pOzMk2Jtdt3PXXWn7bkVK1A1RQoHAzxX+v4vX8al18bNAT1yBo028DDYDNy73+JU8/9JPuqNB9QTL8hxXoiryUq9m2hzFNis7XN9JqnzordBp07K1B0BQoFQ9M7fhrj3/9zT4kVAILSgYYpibEf/4848+TX4sSJEzPfkMJKxCJr1hIZiIrZ1aswJZa2xdn2PXVWzDboXFmBMihQGBiaWvPPMfnT/21rUMFAKB18xlffGcM//vsYGhqasRLpo5oGomJ19ypOiaVtcbZ9T50Vqy06N1agDAoUAoamtz0cF5d90SBUYBDS4DO5dnGcWHJ7HDlyJE6fPh2jo6MzXxk3EPW/y9dhSkxtsZXrqbP+t0fnwAqURYG+w9DVN7bF+EN/bRAqAQhp8Bl77H/FkYFvx6FDh+LkyZPZ4mpbiPrf5es0Jaa22Mr11Fn/26VzYAXKoEBfYSh7auzeP/UaoRKBEIMPA8zb3/tvse+ZpfHGG29kQCQLEWuIvKi6t12/zlNirWBI1z111ts26dSsQNkU6CsM8fi8nxqb/+PvutH3w+WVB+e/9X/Frp0vZUB06tSp4EkzLao2EHX/VuApsbn3HU+ddb9dOgUrUEYF+gZD09uXeJ1QySxCeeiaHFwcR37wmdi1a1ccPnw4zpw5E2NjY9nnPPjGGUDkX3cU8JTY3EFI7ddTZ91pk47VCpRZgb7AEJ/Y4KOqfqHi/G/ourH302VQOX/n78ULz66JPXv2xLFjx+Ls2bMxOTk582JGP3Lf2duDp8Q612c8ddbZtunYrECZFegLDE2t+3ZMrllU+0XTw/u2x/MrlmQb+7OBTavrs4Xt5rXJ534QQ9/7q9i+fXvs27cvjh8/PrOg2uuHOndr6OeUmNrpq88MfKCNcu3QC+s/cL5bba4b/cBTZ51rp47JCpRVgZ7D0M+nx+PCnb+bLcLt1g2TeO/8wmfjpptuytxG6dy36CvZdfw8et9dLW/m3PA//rGPxod//deiUzdkQIj02dgnH7/6K7/8gfyQHn641mjgUVk/8tu/0bIcjbRY6Lnz//z7sfWpx+Lll1/O1g/xyP34+HhcvnzZL2TswJ2hE1NitA022hn1/dSS+xu2tbQt0B4BILVTtS/OKx71I9pmGpZ92i3+5rPl2zlx0Pd+6Rd/IYuX67T72TblMZ+vRseeOutAQ3UUVqDECvQchvj4Kt8ca3RD6uS52//uUxlAcNPPx8sNnpuqQIQbeSvA+fQnPzHjHyjKxznfY+WBGzeDDMfkLf0vXAOOBiP8KtxsrvzPN2/thptY+fV47YHPxvPPPx+7d+/OXsp4/vz57LMdsg6VuI/0LeudmhJT+6GtsE+90jbU1hq1fbUxAIQ+hF/C0C4VjnjoCxzTP/LtRXFwfa4bkJPGB/woDvp2O3Hn40jja7bvqbO+NXcnbAX6qkBPYQhT/+QT/xhTmx98342u2Y1pvud108y7xJeCEDdwbvb4a8fikwJRI8hqlN/Z/nPlmvJI3BwDZsBQeiPnHP4YAFQGBiZtuk44ncNl0GiUp06fu7xrVZy862Oxbt26ePHFF+PAgQPB02UsprZ1aO79u5NTYml7p42r7lO4aNb2AR3akSBd+7Qz2r8slrRN/KZtnbbaDrCo/eddtX9crpG2+h9pUS7ONdrIH2EUh8o8F9dTZ3Nvtw5hBcqsQE9hiIXTo3f8ZtenyPI3Vh2n/yEzAHCz5qaumyeugKPRjZObP+GID7+N/qPOh1Pa83GJKx2INIAxKFAWDT4MCMQPFOncQgaCfBnaOWYh9fqlD8dzzz03Yx16++23s7dTV/XJsutnDsaNSxMd7f+dmBJTfdE+07YNQOgabtofaFPpNUCatk7bStu8jrmuttmobdP+Uhhin/w0a5ecb/QPBueJn3QJTx9I89loX/2hWVqNwjQ656mzjjZtR2YFCq1AT2Ho0mtrY+KR/9nyZtboxjSXc4IG/oNUON1UG9248+ca3ZQVDwOK/Ldzs5VfWX4Ik26zXefmL6sPZUr/M9YNX+EbucpzL9yxJ26PHff/Y2Yd2rFjRxw8eDB71H5iYiJ7sqyK7x2a3vRAjH7jtwJ3oVDUqSkx1TXtVG2HtgG46Frqqk3hh/5Cm+M6sCPwUdsCrDjHputc45g2rbhIF/hJYYg+JahK0yGtFKryfYpjpYFf0lJ+8i7XUj/5uLg2n81TZ4Uew5w5K9ARBXoGQ5npf+P9cXHVP83rhjSXm5hurrpxpjfJ1KLCzVIb53WDny0tbuq6CTM4tPpPVX4ZGBrFm79O/IozBS/5w8WPBhtcDUIMNul59jW4NUq7k+emN90fB77zl7F69erYvHlz7N27N956663sRYyXLl2q5EJqIGjkSx/KtvlCUSenxFSf1LssQrSXZiAk/4IU/LIvCxLxpNfoR7Q1rqdtU9CBf+JQf9Mx59hXO1U6tE3iUV6BqHx7Je40TvVp8sU+m6BP6cqP8qVyLtT11FlHxhxHYgUKqUBPYWhy2ReDQXOhN6VW4YEabqD5G6lgRzdRXN34ARD8txo4dKMlfjZu8LPlJ/VH/OlGON3IAZz0WPnguvyoTPk8KI1GLoPQbPnr1LVLO5fF8bv+JAYGBuLZZ5+NV199NY4ePRospOa7ZVWcKkthaD5Q1MkpsbQeU4BhP21zjfbVX9R+6BNpGxPECFrwl7ZJWWCJm2u45CcPQ5zTPyqKQ3Hiqi+mZVGc5Ifzylfarpv5UT7S+Ba676mzQo5jzpQVWLACPYWh8R99OvjvaqE3pFbhdcPUmggGBGBH53F1M9eNVDdurjWLX364kesmzr4sOY3Ccb3Zhn/liXwov/k4dZ5yEIZBg7y0s+X/026Ux06cu7L/2Tj1jd+LpUuXxtq1a4OpMr5bNjw8PPMSxqq9kboRDLUDRZ2eEsvXH3VOW1Ebb9b+0vO0Q6CHtkZ8AA5tHHhR+8MPbY54iV/hOVYYzgnk0/7CvvKZApHiUBj5kav+qX6p/kJeucamc3k/XFM8nXY9dbbgsccRWIFCKdAzGGIgHPvef+nJt8h0c9SNFje9aXJj1n+7nOe6bty6oTa6eWoAYJBIp8tmC6M86OatdDlPGsor/50LsNhX+oCPzqf/OSve2dx0AFJ83XKvHn0p3v7qf4gtD3whXvrR1+P1ny6OY0/fH8ObHo4L25+Iiy8vD16rwMbTZ1XYJh/7zMw0mSAo7+anz6aefzDGvv2xrj9RST3LEqp2S1thnzanTW0r34ZpO0CVQEjAQ7ycZ6PvKG7+IVBc+udAfYp007ZI2BTUCDdXGGrU7lUGXK53E4bUj1pNnVVxrVyhRjBnxgp0SIGewtCFb/1uTz7BkR8EdLPVTTK9kbYLQ/KX3mTT+JrdzJWWBoN0gOCGmsaLX/LKYKGbrQYYXKWXxsG5/KYwSlNxddO9vPvplmCQB4U6HV+4+w9j4vt/HuMP/mVcHdo5U7/drBPFnbYxnZOrNoWrc7g6r/abd4kTf/Q1rgluUmhK26naYgr3au+Ku1EfUt6VP+ULSCNONv2DkfejPKbl6sY+U2fjD/33OH/fn2WvlOApSj5Jw1o5TQ+zNsw/K2AFiqtAb2Ho2x8LplO6cUNqFKduxo1ukrqp6mab95vGp2u66QtW+A9YN3IAJLXcKLyuEwfnZFHCP8cMAPKDy01e/1lzXf95p37S/ChOyiOLksqmNPHT7e3qm7ti5Msfjufv+1y88OBXYvdPvhWHVt4bp575YYxsfSwmX1oW06+sqLVl6ProyZj48d/G+EN/HUyzdLtOFL9ggTakc3LVVnB1Dpe2lAIO1+VX7RR/tPm0baYAkrZT9mn7AnXC0PbzcJQHIvVP5U95KAoM8X3FCz/62zjzL/81Xt8ymE0NnzhxIlsrBxDpPVtVmyIu7pDmnFmB+SnQExjivyJuBuM/+KtgoW160+3GPjdQbuYCCW7ADAi6keLqRq+brW7cuukqX/mbtRY667rCc3PPA1EKS7p5p3kgDsER4ZU2eWOf8FxnI39AGFsaL3Hov3MtZFUahFE+u+0yuJ+543diyZIl71tEPTQ0FPynPD09nf2XXKX/kOe6Zog+gKXg4r7nYvSe/xiTq+7o+ju3aC8CELWvtC2oH9A/0vOE0zXaF8e0Ydop5zmWf/njWnpefYrzCss++Un7Ub6Ppe1W/Ut5V9smnvyW90NY5bEb7thT34yz37oltv3wjuyVElu2bMkeHGCt3MmTJ2N0dDR7eEBvYa9S25/fcONQVqC4CvQUhiaWfqEnT5Plb5Icc6NsdCPVzVY3bt1QuXnmb9IMCo1uqoIu0kmBKLX6KB3ljcEnH79u3vLz1CPvQBDnAR0NOmlc6aDFddIkn5SD+BvltxvngNw3//mPMxhavnx5PPPMM/HKK69kT5SlL1+s0oDQCIbya4TU9fUPAQMjT9eNnBuOsysXxcjiP+zaQwW0jbRt5q0utAO1NbU9tQ2Amzan6wKqtH3jN7U64TeFKvUpzrMPENFGG7VL9YV8HtXW1S/VhykX++mm/ik/+TKpbAt1aevnFt0Sr37n0/HEww/GT3/601i5cmVs2LAh+2Axr5Xgn4Bz587NPDxw/fr1qFLbV7u2awWqokBPYWhy8J64+PS3uj5AcxNk4+bIjZgbJzd33SS5Geomq/9CdePGD9dTkCEOnW90IyVuDRb41YChwYT0FT/XOc9/xmkYhVOeOWaAwM1vDCqEZ+ARIKV+iJfyka9G+e3GOT6xcmDxf2sIQ+nj9VUaEFIYagZBulHkYQhAPH78eBx8+fk4/b0/i5Hvf7KjU2e037Rt0Aapd4Ey7SMFGY7z7YI2qzacti/ipf2pP3EtbcukRdtN2zzn8C+X/fyWv0Z+1E/xm+Y/BarUGkWbV7kblSlfxrkcMyU28tCnYmjRf4qfPrA4fvjDH8YjjzwSjz/+eKxYsSKzDm3bti1ee+217J+As2fPGobUAexagYIr0FsYeuHx7Ntkc7kBLcSvbsa6keJy42YQ0M1bg4ZuoNz8STMdKLhJpzfcRnnSf7bETxz41wCi/1gVLoUc8kE+lb7CKB+cJy8AEP7IL/mRP1z8ECcDVD6eXgERH2t98Z6/fR8M8a6hY8eOZdNketdQ1WCoFQSp/wuGmCZjypApFKZSmFJBp10D34+zi34/xld8fcFTZ3mQT9tvI7ihDaVwQTvNtyP6DnBBe+Wa+g9hFb/6F9dod+p/aVudyz75yMOQ+lDq5surNDif+lvIPlNiw3d+JNb+y23x4IMPZiD08MMPx09+8pPsdRK8bHTjxo3x0ksvxf79+zPQ1ceKr1y5ki0TqFLbV7u2awWqokBPYejy6JkYvfN3OnaDanVz0804D0O6aXMTJw7dPHEBCsULhAhsdG42V6AicCJ9DQz5cPjlmgYhXA1AnCdsPgzHKWThj8FC6cm/4hZQ6Xw33fPf+b9jxX3fjEcffTRbM8TAsGvXrmy6YGRkpJJrhub6bTIGQ6ZLWFTLZ0oYLLEO/exnP4udO3fGluc2xv4H/zHOLfr9BU+dCebz1hHaBu0/3dI2rzaCP9oj8aRtkbbGMe2V/gLop+1P4E48ABHpz3cjDsKSjvqw8pe6pJP24Vb+07Ct9jUltvOe/x4//v734qGHHoof/ehHGfRjEWJKeM2aNbFp06bs3Vqvv/56ZhU6c+ZM9qFiP1FWlaHS5ai6Aj2BIURk8Sj/IV34/l/0ZBE1N7n0xs0xN/D0xt7qRpje5Fv5bXZ9tjgaWW3I32xhSIfBSxA1W7qt4mkWdq7ntXiaaQP+U2b9BB9sZbqAwR4rSFU/yTGXG0RqHUKP8fHxbF0Jny3BQrR79+5szcmWp5+Mt77ziXj7gT+f99QZdd+ofc21bmfz3+34SZs0BF+z5QU/bJ3KUzol9sT9dzW0Bj311FOxfv36YOE06+OwCLFWiBeNXrhwYWbxtNcLzaWX2K8V6I8CPYUhFo+OPfdQTC79QkOrx2w3O1/r/uPx89V4au3ieGXxX2f/MfPfMlMGDBD8l8xjxmNjYzOPGNd9qkBARF8AiHj8GsvZqVOnMosCA2pmJdqyJXY8cW8Mf+uWjkydzbdu6xguPyWGNejHP/5xZvVksTTrg3jLOsDPm9aB/sOHD2dtnUXTQC5TofzzBwj5sfr+DG5O1QrMRYGewlD2WPHpIzH6z7cYhnrw7p9eDWTn7/2vsfJ7XwvWUDBYDA4OZhaOAwcOxOnTp7MpIa+beK9bCojoD+jCeiqAkYEUeDx06FA2wDLQPr/xmY5NnfWqPZQ1nXamxJ5++uns23vbt2/PpoFp42+++WZmDcICqpctAruyCNX9H4D3Wr73rEBxFegZDHFD4ObAf8MXfvz/xfS2hw1EFQCiy68NxslvfTRbS8E7hpYtW5Y9Yvzyyy9n/y3zRM3FixeDwcH/Ib93IxAQ0SdSKxEDKutNGGAZaFl3xcDbiamzskJKt/M91ykxLHdY8PgQMRY9ngxkDZisQUAubd0Q9F57954VKLoCPYUhbhAsHh07PZRZh3iNfbdvdI6/u9Nr5+/+o3jyX+/MpsjS9UKsf2H9RFUXT3eqYwuKZCViQGVgZYD11Fl32y73hvlMiWG5w4KHJQ+LHpY97mspBBmEOtVDHI8V6I0CPYMhigMM8V9wtk5i2dfj4tq7DUMltg5h3Xvjnz+eWYU0RcaTNVgy+M+ZR8e9Xqh1R2bgTKGIgdVTZ90FoYVMiWG5azQlZmtQ67ZuH1agqAr0FIa44fPfE//9jpw+HqN3/1FPPtxq61DnBxasenyK4LEH7sneuaJH6nnzNNMILCjVS+c0Reb/lme/DQiIPHXW+faqe4CnxGZvg75qBeqqQM9hiBs9i0azx4pfejpG/+0vbB0qoXVoZMnfx3P/8tn3WYVYXLp169bsKTIeF+e/Z8AXADYItX+LERR56qyzUOQpsfbboH1agbop0FMYQlxMydzkmQZgXcSZVXfHxLIvG4hKBETj674Te+/5i+zdK7yAjrVCPG787LPPzliFeNcKa1/8FNn8bikAUQpFnjqbPxh5Smx+bdChrECdFOg5DHGDxzrEzR3rEPPvZ3/4P+Pi8w8aiEoARAwsR+/6z/HQvz2QTY/xBNnSpUuz966wVmjfvn2RtwoBwP7NTwEBkafO5g5DnhKbX5tzKCtQRwV6DkOInFqHeNroraGjce57/4+BqOAwBAi9tfhPZj5LwEcqea8QL1l8/vnnszco87ix1grZKtS5W4qgyFNn7UGRp8Q61/YckxWogwJ9gSFZhxgsebKMR1SPHX4jTv/gb2N85ddtISogFDE1hkVI32fi6THeNr1q1arsA5W8V4hPSvA4OE+Q8T4pBm5bhTp3G6HfpFDkqbMPgpGnxDrX3hyTFaiTAn2BIQSWdUjfaGK6jPd3vPnYV2PkB3+z4C936+kRux8cMOaqCYulWSPE1BifJhAIsU6Ip8defPHF7FF6psew9LEezE+Qde82IiDy1Nl7bdtTYt1rb47ZCtRBgb7BkG7oDJo8ccSTR7yX5uDBg/Gz1T+I83f+Xkxveu8L8nMdwO3/vYFivlrwHqFzi27Jnhp78MEHszVCTI1hEQKENmzYEC+88EL29BhvTOYr7Fj6sPgxUFPH/nVPAfWhuk+deUqse23MMVuBuijQNxhCYN3MGTz5ZANWBd7smn2GYNvGGHrgb2Pk2x/r2Vfu5wsNVQvHJzb43hgvVOSL3ViDeGqMxdKsEWJqDIuQQIg3TTPVydNjTN14eqx3tw/6kPoRutdp6sxTYr1rZ07JClRdgb7CEOJyI8eKICDicXsB0SuvvBI7Vv8kTt7zp/H2v/znmHrmu3H14PNeU9SFNUVMM2CJO3//n2XfGltx71ezR+d/+MMfZtNiPD7PU2MsluYReqbG+Co9IMSCaZ4MTNcJUa/+9U4BAVEdps48Jda7duWUrEBdFOg7DCE064cEREyzCIhYkMuHKnmR3/ZlD8bB730qhr/xu/H2Pf8xptYuzixG/Hfob5zNbUoMvdCNDR2xAp37p9+M1xf/Way+98szliDWBvFmaaxBTIvxNfrnnnsuWCzN5zaYGjMIFetWISiq6tSZp8SK1d6cGytQFQUKAUO6gQuImDJjDRFPJh05ciT27t0bO3bsyAbitWvXxjOPPRB7v/u3cfyuP8m2ouFx3QAAIABJREFUka/8+xj50oe8tavBV/59DC36T9n26t1/E6v+9evZeiCmwgAg1gVhCQKCli9fHrxZmmmxbdu2ZXDKui4WS7NGiKkxW4SKdTugP6lPVWXqzFNixWpjzo0VqJoChYAhRNXNW0DEE0kXLlwI3mSMBSJbR7RrV/YR0I0bN2Yv+WPtCoM1gzaLehnAWdfCYM6gnm4//vGPw9s7GqS6oBWaYQF67LHHMi2ZDlu5cmXw0VUgaMuWLdmbpZkW4z1CQCrru7DipWuEqEP/iqNA2qd4UAFopc74R4OnN/P9asvTT8Zb3/lEvP3AnxdmOtpTYsVpT86JFaiyAoWBIYnMDTxd94DlgWkzBmAGYqZnXn311WzxLi/6Y7Bm+oa1LAzgAwMDsWzZsmx9y5NPPpkN7sCStw9qgD6AD0DJNNhTTz2VAdD69etj06ZNmSWIj65imeO1B1iDmBYDUoFV1nlpsbRBSC24eK6gqGxTZ54SK15bco6sQFUVKBwMIXR688bywLQZL/LjiSUevweKsBS99tprmcWCp5qwXrCehcW9PPK9bt26zHoEKHn7oAZMN6IR4ANQAj+bN2/OLG8vvfRS9jZpwJOvzx8/fjyz0MkahIUBSwPQynovg1Dxbw/UUb5fAbTqVzy0APDSp5iSfn7jM7H/wX+Mc4t+Py69+HhPH1rwlFjx25NzaAWqpkAhYQiRdeNOrUSY+LFKsFbl9OnT2SDNmiLAiG9i7dmzJ7MaYc1gQOemzlNP2oCmOm/SARdt0AitsLTt3r07swD97Gc/ywZFnhIDPLEEAUFY6HgflK1B5b4FNOtXRZg685RYuduWc28FyqxAYWFIourmLRM/VgksRTzKzSCNtYj1DwzcWDAYxLEcYdHgP12eSGNj0a+3dzSQJugDTB47dixbP4J1gOlIAIipSawGAGgegmwNUussr5vvV9RxoylpYBmr644n7o3hb90S4yu+3pWnNz0lVt625JxbgSooUHgYQmRu3Lp5y1LE9Bk3cMCImzgDN//dAkhYjoAkBnUWYHv7oAZow4ZWgA+6YXUDMgVAaJxaggxBVejy75Uh7Vf9eurMU2Lv1Yf3rIAV6J8CpYAhyZPevIEibuCsXWHAZuDGagQgsRYCSGJjYPf2QQ2kD1qxoR0bWqIp2mpNkCFILbCabv4fDdoBfaabU2eeEqtmW3KprEBZFSgVDKUip2DEYM3ALUBiIBcoMbB7a66BtGoEP9I41d371VVAUERbAIq7NXXmKbHqtiGXzAqUVYHSwlAquAbt1AWQvLWnQaob+/7VVwG1BfoOUITFtVNPnXlKrL7tyiW3AkVXoBIwVHSRnT8rUDYFgCJZXLGsLmTqzFNiZat959cK1E8Bw1D96twltgJtKyAomvPU2fKvxvTz34+xlXfE8J0fiXXfvT375p0+/Jt+8453XvGOMF73wHuOeMqRJxt5CIIHI7BMYaEiDwCarFdtF8IerYAVsAItFDAMtRDIl61A3RUQfMxl6uz44j/NvhU49K0/jCeX/DD75Is++/LEE0/MfPOOl6Ru3749++Yd7wvjEyG8KoPF2yzixiKFZUqL+cmLf1bACliBTitgGOq0oo7PClRUAVmJAJNWU2dHv/8/Mhg6cO//m33qhU++8JkcPpfDp3N4S7y+ecebzvXNO17z4Bd8VrQBuVhWoMAKGIYKXDnOmhUoogKCotmmzk786O8zGDr6wK3Bh5WBHz79giWIz77w9nO+ecfLUT0lVsRadp6sQL0UMAzVq75dWivQEQVaTZ2d/cn/zmAIKOJzLy+//HIGQK+88kq2Loi3oDMlxgtRPSXWkSpxJFbACixAAcPQAsRzUCtQdwVkJcpPnY389PMZDAFFTIGxKFqff+GzOawL8pRY3VuPy28FiqOAYag4deGcWIHSKiAo0tTZ2LIvZTAEFPHJF30ahyfE+PQLn33xU2KlrW5n3ApUTgHDUOWq1AWyAv1RIJ06mxj4SgZD48u+lEGPPonDZ2B4szWPyvspsf7Uk1O1AlbggwoYhj6oic9YASuwAAWAoskVX81gCCgCetgaffcOv/5ZAStgBfqtgGGo3zXg9K1ABRW4+C4MAUW8nyi/GYIqWOkukhUosQKGoRJXnrNuBYqqgGAI1z8rYAWsQNEVMAwVvYacPytQQgUMQyWstB5lWWvL5Oathj7+oCW1LJqoTlO3R81qwckYhhYsoSOwAlYgr4BhKK+Ij1FAg6QGd17J4K1aGqhucVXfZWj9hqEy1JLzaAVKpoBhqGQV1oPsMjAyQAp+eA2DFtbzdKE2vkfnrRwaqM7k6iEJ6pX6pa7LAkWGoR7cBJyEFaibAoahutX47OUFhKY2fDem1t4dF9kGF8ektjV3xeSau2LCW6k1GB+8J/TqDGBWYJQC0eytpL9XDUP91d+pW4FKKmAYqmS1zqtQsggBQtdO7fdWUQ3GVy/KXqh64cKF7GPLeqkqVqIyAJFhaF7d24GsgBWYTQHD0Gzq1Oea1owwGGIRMgxVFwZHV34zTp48mX1qh7fOA0W8bBUrkYBI7aGIPcAwVMRacZ6sQMkVMAyVvAI7lH1ZhTIYGlxsGKqoVQjIPT9wR/b9waGhoQyK+PQOQMTUGVNmrCHS+qEONa+ORmMY6qicjswKWAEUMAy5HaCAYIiBkHVCtgxV1zI0vPRrsXv37ti/f38cOXIkTpw4kX2XkO8QyjpkGPJ9wQpYgVopYBiqVXU3LaxgiGkSFkwbhqoLQ6ee+HJs3749du7cGfv27YujR4/G6dOnY3R0dOajzEVeO2TLUNNu7AtWwArMVwHD0HyVq1Y4wRDTJDwxZhiqLgydeOyLsXHjxti2bVvs2rUrDh48OGMdYu0Qj98bhqrVv10aK2AFWihgGGohUE0u671CDISGoeqCEJB7/NHPx5o1a2LTpk2xY8eOzDrE+qGzZ89mT5cxVWYYqknHdzGtgBV4RwHDkFsCCqQwxHuEbBmqLhC9ueRzsWrVqtiwYUM2XbZ3795sqmx4eDhYNzQ9PV3oRdSeJvM9ywpYgY4rYBjquKSljNAwVF34yYPt0CO3x8DAQKxbty62bt0ae/bsyRZSnzlzxjBUyt7rTFsBK7BgBQxDC5awEhEYhmoEQw/fFsuXL4/BwcHYsmVL9mQZT5WxiHpsbMyWoUr0aBfCCliBOSlgGJqTXJX1LBhivYinyaoNRscevi2WLVuWrRvavHlzBkOHDx82DFW2d7tgVsAKtFTAMNRSolp4MAxVG4DSqTJgaOnSpTMwxBNlhqFadHMX0gpYgWYKGIaaKVOv84Yhw5CnyerV511aK2AFEgUMQ4kYNd7tJwwN79ve8afXDr2wPp5fsSTbUqtIv/bJTzfKOZ/y2DJU447uolsBK9BYAcNQY13qdrZfMPTofXfFr/7KL8d9i76SARHAIIhp5QoECPPxj300Pv3JT8xA1Ud++zfipptuil/6xV+YOSf/eTcFp1Zp6no+Do65Rpps6XXyRxk5n+Yx9dPLfcNQ3Xq3y2sFrEBLBQxDLSWqhYd+wRAQI2h59ZmB9wGFwKKZK4B4asn9MxAi2BAM4cpfM/fOL3x2JnyztPLnG8XVDIbS+G//u08Fx+lGuEbxdeucYagWXdqFtAJWYC4KGIbmolZ1/fYLhrCaYL0BNj78678WABEAo41zAhGdk5vCApChOIgTPxzjpv4a7aeworRauWk8pAfQYN1SOI6xOFEenWvmkn4aX7f3DUPV7ccumRWwAvNUwDA0T+FKFOz6mYNx49LErDnuFwwx8AMRTCMJIDgWIHBOECFIwJqEHyCEaTZZWYAqWV40LYWr63mXsIpTriBK6et8Cm35a2kelVdcrFQCPdw0faWDv0b5ULrdcA1Ds3YFX7QCVqCOChiGql/r05seiNFv/FbgNoOifsIQAz6wgQsYAAjAA8cpaHCsKTGuEyaFihRE2tlvZDVSfPlrsjwpXfKiLc3jbOlqCg9rEfHgN5+O4uymaxiqfp93Ca2AFZijAkWBIT4LoIHk5ptvninFrbfeOnP+8ccfnznPzqJFi7JrhNXv6NGj2bk0Dq7pPGHm8rvllltm0k/DkhfllzymP6X1x3/8xzN+5DfvEn/+pzLny6vzef+tjoGgkS99KNuaQVE/YCi1lKTWFoECYJSCBoCgNUYCCyAFoMhv0hnLUP6a4k/TFHzgV2FJW+d1Lo2PtHUdl/jkj2Pyj38BHteIX+kzBSgITOPp9r5hqFWP8XUrYAVqp0ARYCgFIQYMgUwKHBpkAA1+CqNjVRz+AAziyINGszAKm3eVPmmk+4Id5Qk3BRfSTsFJ8TaCN12TKz8CnxT08EOZ8vClsM3cFIaaQVE/YCjVj31BAKDDMeCTwhBrcBSGffnPu6k/QCR/XcDTCIYEKqSDP4VVuqmbXscf4KPrKeSQH0GcruOSt9Sf0uq2axhq1lN83gpYgdoqUAQYmm3gZ9DgJxgRdOShQNcVF8dAicKrgvPhdL6RKzDhWgpSOs85gZEARfloFJ8GwkbXOKf8Ehf7iov09EvzoXOt3EYwlIei61Njcf369ejl5ziAEYEP2ggCACDOMyWWwhDgoDDy28hNLTGKK4WOZjCEH9WRXMKTBukqbV1LLUNpPrkOVFGGFJA4ny4IVzz4mQ3uGpVxIecMQ616jK9bAStQOwUEQ+MP/U1c3rWq5xuLexn4gRQ2BgiBhc5TKYIOgQH+gAV++GPTLw0neFCchE/9KkwzV3kiPaVNXBzrl6bHNcLkf4RNy5ZeF/SoPDom7/yUBzTgl5Yd/VrV2+Rjn5mZJhME5V2mz6Y23h/TF8719NtkKUSk0NEIPnROrkAlDwYCLIBE8JFOSQlQiCcNm+ZFfnBTkJKFh7hTgBFgUTf5TWCk/BIOkFIaXE/z0e19w1DWjfzHClgBK/CeAtPP3NtyoMwPnJ08xmoBTOQHEEAghYwUhrQvWKA0Aoh8PBynP/nTOUGK/HEscJJfzqVAMhsM4U/hlYbyq7wRH1v+10gHwuT94k/nZrP6zKeeRhf/QUwMfLVng3MKIECANGrHzcMM4QENhQWK0kfbgY7U+oPlKQUPAIWw+EvzRTz4Sy1OadpKg3BKm7iIHxe/zTbiFiSleenmvmEo3/N8bAWsQO0VwKrAoImFqJWFoRvXZRkSQMiSA4gIQKgkgQmu4CKFoXxFpv7Tazqvc4AF8ShdBjPi50f6bPpxTSDDPmGUF+W/EQw1gxyFUfx5l3Bs+R/nBEO2DL33VBcAIcsN9SPIEMTg4odr6XWBhyw1xME5wRF+U8sPViaFwRWAySKFf11PwyndvCu/vXINQ/ke5WMrYAVqr4BgCLdfPwb2/AABZDQ6rzziH7DRrxlw4C+FDsWpcLO5gI1gRLBEmtpP88w5fqSVApTyRbpp2tqXX0FaGme6L0AjDc4Tvt3fbNYjPV3WjzVDDP6pBQYLSx400uutYEHQgz4CGoVJp7Skq2AJP2lYQRPnNc2mMFh/0rgUP9DTKK+CIdzUOtQInBRXt13DULs9x/6sgBWojQJFgCHEBgo04KSQk54XcMh/CjmptSStPMKn/vKwkvpttC+YIW9pPIIZzqdgIqghLvkRyOhY6XCchyFdkyvwUhy4pJlqIb/N3EYwJAjSe4f68TQZg34KEKr/FAbS6+n5/H4KM82AJZ8e8KV4ZBUirM6RdiMYSmFJfpl+a5RXwRAgJL+4jfym17u5DwwtW7Ys1qxZE5s3b45du3bF4cOHw1+tb9aDfN4KWIHKK1AUGJqr0Cl0EDaFFg2qcgUx8wGJueYL/6SbAp3iyMOQzuOqPMpz3hUMzRXmiDuFoTwEKQ9FgSEsOumC5XagIf0MBrppLRAWHCBET6XhptNoAo40PP5JUxCjekjXA3GOY60LUjyN8qp4gC32taWQpfC9cg1DavV2rYAVsALvKlBWGCL7shq1W5kAkywx7YaZjz+BTR6IZoOhdtJRvHOxChEvMNQMgpRuv2BIIAJcNLK4NAKMFBrS6SYgJR+HYCbvAiXEo/U+AhzBS+pfVh1gShYkXedY+WmU10bxKaxche+V62kytXq7VsAKWIF3FSgzDLkS21OARdaaDmsWol8whBUIYEinrFIoaAQY6XXCY2UBpvCbXmM/DyPACwCVWp80xQbscF5WIPw1Wh+Ef1l20jQb5VXpExfXtQkCAaJ8nrt9bBhq1gt83gpYgdoqYBiqbdW/r+D9gqFWAz9wIoBo5hc/Kdw08zfbedLQdQConfjyoNQor0AecbfjV+l32zUMva/p+8AKWAErENnj9DxaDxT5V18FigpD3QaDOsZvGKpvP3fJrYAVaKKALUNNhKnZacPQ+99XVGVIMgzVrHO7uFbACrRWwDDUWqM6+DAMGYb8aH0derrLaAWsQEMFDEMNZandScOQYcgwVLtu7wJbASsgBQxDUqLermHIMGQYqvc9wKW3ArVWwDBU6+qfKbxhyDBkGJrpDt6xAlagbgoYhupW443LaxgyDBmGGvcNn7UCVqAGChiGalDJbRTRMGQYMgy10VHsxQpYgWoqYBiqZr3OtVSGIcOQYWiuvcb+rYAVqIwChqHKVOWCCmIYMgwZhhbUhRzYCliBMitgGCpz7XUu74Yhw5BhqHP9yTFZAStQMgUMQyWrsC5l1zBULxhatmxZrFmzJjZv3hy7du2Kw4cPh2GoS53L0VoBK1B8BQxDxa+jXuTQMGQYMgz1oqc5DStgBQqpgGGokNXS80wZhuoDQ0MP3xZYhgYHB2PLli2xe/duW4Z63uOcoBWwAoVSwDBUqOroW2YEQ5cvX46JNXdFlT9UWveyAUMDAwOxdu3a2Lp1a+zZsyeOHDkSZ86cibGxsZieno5r164FbeLGjRt9a5PNEr6p2QWftwJWwArMVwHD0HyVq1Y4w1B9LENvPnJ7rFy5MtavXx/btm2L1157LY4ePZrB0Pj4uGGoWl3bpbECVqAdBQxD7ahUfT8pDI0P3hPjqxfF6Ko74+2BO2J46dfi9BNfjhOPfTGOP/r5eHPJ52LokdsDC4O3EmnwyO0BCB148B/i6aefjo0bN8aOHTti3759MTQ0FGfPno2JiQnDUPW7u0toBaxAXgHDUF6Reh4Lhq5cuRIXL16MkZGROHnyZBw6dChbU4IF4dlnn80GUawKy5cvj6VLl8aTTz7prQQaUFesE1qxYkU89dRTmVWIJ8l27twZBw4ciOPHj8e5c+dicnIyLl26FNevX/c0WT1vBS61FainAoahetZ7vtSsDQGIrl69mlkGWDsyPDycWQz2798fr7zySmzfvj02bdoUzzzzTKxbty5bc8IiXB7R9lZcDagjNtYIbdiwIbMIsVbo5Zdfjr1792brhU6dOpUBMCDMujHDUL6H+NgKWIFKK2AYqnT1tl04wRALZ7EMMF1y/vz5zDrEO2hef/317H00TKsARQymPImEdcFbOTSgvrDwvfjiixncAkJvvPFGZhViikyLp7EOAsa0CS+gbrsL2aMVsAJlVsAwVOba61zeNfABQwyGU1NTceHChWzq5MSJE9kC24MHD2ZQxIJbnkDikWxe2Oet+BpQV2zUHWDL1BiQy/QYFsDR0dFsigyrUJGfJKPF+2myzvV7x2QFrMC7ChiG3BRQQDDE9AhTZQyKTJlgLcBCxAv5gCIW2h47diyDIx7HZkD1VnwNqCs26o46fOutt4KpMSxCgJAWTlP3tAG1hyL2DsNQEWvFebICJVfAMFTyCuxg9hkAtZCaQZHpMoCIx60ZMIEiBk8sCbyTBkDyVh4NqDPqjjqkLlkkD+yyaJp3C2ERTK1CtIci/gxDRawV58kKlFwBw1DJK7CD2Zc1IAUiLEQMlEARgyZgxADqrbwaUIdYgqhT6pY6Bn7LAEI0d8NQBzu9o7ICVuAdBQxDbgmpAnkgYoBkoMRqwKCJtUgbA6m3cmmguqMuqVNBUPr0WFEtQmqnhiEpYdcKWIGOKWAY6piUlYkoBSJZiYAibQyg3sqtgepSEFTkp8fyHcswlFfEx1bACixYAcPQgiWsbASCIrkMmN6qo4HqVW5ZGrJhqCw15XxagRIpYBgqUWX1KasaLO2+896dqunQp2Y172QNQ/OWzgGtgBVopoBhqJkyPm8FrEARFTAMFbFWnCcrUHIFDEMlr0Bn3wrUTAHDUM0q3MW1Ar1QwDDUC5WdhhWwAp1SwDDUKSUdjxWwAjMKGIZmpPCOFbACJVDAMFSCSnIWrUDZFDAMla3GnF8rUG8FDEP1rn+X3gp0RQHDUFdkdaRWwAp0SQHDUJeEdbRWoM4KGIbqXPsuuxUonwKGofLVmXNsBQqvgGGo8FXkDFoBK5AoYBhKxPCuFbACnVHAMNQZHR2LFbACvVHAMNQbnZ2KFaiVAoahWlW3C2sFSq+AYaj0VegCWIHiKWAYKl6dOEdWwAo0V8Aw1FwbX7ECVmCeChiG5imcg1kBK9AXBQxDfZHdiVqBaitgGKp2/bp0VqBqChiGqlajLo8VKIAChqECVIKzYAWsQNsKGIbalsoerYAVaFcBw1C7StmfFbACRVDAMFSEWnAerEDFFDAMVaxCXRwrUHEFDEMVr2AXzwr0QwHDUD9Ud5pWwArMVwHD0HyVczgrYAWaKmAYaiqNL1gBK1BABQxDBawUZ8kKlF0Bw1DZa9D5twL1UsAwVK/6dmmtQE8UMAz1RGYnYgWsQIcUMAx1SEhHYwWswHsKGIbe08J7VsAKFF8Bw1Dx68g5tAKlU8AwVLoq61mGb9y4Een285//PLxVQ4O0XrXfs4a1wIQMQwsU0MGtgBX4oAKGoQ9q4jMxA0GCn+vXr4e3ammgusUtExAZhnyHsgJWoOMKGIY6LmnpI2RgZIAU/Fy7di2uXr0aV65cicuXL89sly5dCm/l0CCtN/apS+qUjfqlrssCRYah0t9iXAArUDwFDEPFq5N+5ggQmtrw3Zhae3dcZBtcHJPa1twVk2vuiglvpdZgfPCeuHjxYkxPT2cwKzBKgaifbbBV2oahVgr5uhWwAnNWwDA0Z8kqG0AWIUDo2qn93iqqwfjqRTEyMhIXLlyIiYmJmJqayqx9WInKAESGocreglwwK9A/BQxD/dO+SClrzQiDIRYhw1B1YXB05Tfj5MmTcebMmTh//nwGRZOTk5mVSECk9lCkNqq8GIakhF0rYAU6poBhqGNSljoiWYUyGBpcbBiqqFUIyD0/cEccOnQohoaGMig6d+5cBkRMnTFlxhoirR8qYqM2DBWxVpwnK1ByBQxDJa/ADmVfMMRAyDohW4aqaxkaXvq12L17d+zfvz+OHDkSJ06cyCxE4+PjM9Yhw1CHOpajsQJWoBwKGIbKUU/dzqVgiGkSFkwbhqoLQ6ee+HJs3749du7cGfv27YujR4/G6dOnY3R0dGb9UJHXDtky1O27geO3AjVUwDBUw0pvUGTBENMkPDFmGKouDJ147IuxcePG2LZtW+zatSsOHjw4Yx1i7RCP3huGGnQSn7ICVqC6ChiGqlu3cymZ3ivEQGgYqi4IAbnHH/18rFmzJjZt2hQ7duzIrEOsHzp79mz2dBnvjjIMzaX32K8VsAKlV8AwVPoq7EgBUhjiPUK2DFUXiN5c8rlYtWpVbNiwIZsu27t3bzZVNjw8HKwb4v1DRV5E7WmyjnR5R2IFrECqgGEoVaO++4ah6sJPHmyHHrk9BgYGYt26dbF169bYs2dPtpCaR+0NQ/W9B7jkVqDWChiGal39M4U3DNUIhh6+LZYvXx6Dg4OxZcuW7MkynipjEfXY2JgtQzO9wjtWwArURgHDUG2qetaCCoZYL+JpsmqD0bGHb4tly5Zl64Y2b96cwdDhw4cNQ7P2EF+0Alag0goYhipdvW0XzjBUbQBKp8qAoaVLl87AEE+UGYba7ir2aAWsQBUVMAxVsVbnXibDkGHI02Rz7zcOYQWsQEUUMAxVpCIXWIxuwtDwvu0dfzrt+RVLgu3QC+s7HndqRenl/qvPDPSkLLYMLbCzOLgVsALVU8AwVL06nU+JugFDgMqnP/mJ+NVf+eUQEDHgC2Rmc1PIeWrJ/VkcggXC3XTTTdl236Kv9AQgZstro2tp/lOg+shv/0aW7zu/8Nn35ZtyqEzNwqbxLGTfMDSfHuIwVsAKVFoBw1Clq7ftwnUDhoAXDfBAEQO4YEDnm7kpLHz4138ti+eXfvEXQjClcIBIKzBoN03FmbrKR3qunX2Fy+dNeUmvA4qUjXgpK9fyWz6ehRwbhtruFvZoBaxAXRQwDNWlpmcvZzdgiAGbQV3wgIXn9r/7VAZEQAGbIADrkc7hPnrfey9+xFIif5xPLUNlgSFBnMAOOFTeP/6xj85oJK3y7kLgJx/WMDR7X/BVK2AFaqiAYaj6lX79zMG4cWli1oJ2C4awegA6QBD7ABEgoKkgwIeBX5YSXQcU8CMLCcAgqwnhBQvsy0/eVRoCEeJMN/KkeAibXtO+4hBQcF5hdE4ucXANcNO0oK6pnAorN80DZUzLID/op3g64RqGZu0KvmgFrEAdFTAMVb/Wpzc9EKPf+K3AbQZF3YIhBu8UDBjYGeS11keQAATgV5YTwYmAYD4u4NIMHsiTrE1zgY0UhtL4gSbFp7Kkaaucs5WD8IAb4VLgS9NJ45zvvmGo+n3eJbQCVmCOChiGIh5//PGZ//ZvueWWGQXZ1+DFZwvK+gOCRr70oWxrBkWdhiEG8NTKoQFdC4UFIIIE/AIC0hu44Jjr+U1Ahd/8NcEU12aDhdQiw/5sftNrlEN5JG1dI//peeVLcCN/8oN/gIz8oonyDRARVv7S6ULFsVDXMFTWnux8WwEr0DUF6g5DKQgxAAmGFi1aNDMgaWDKVwLnCY/fm2++OX+5MMcpDDWDok7DUAoH6MQxgziQIz0FO7ouawjubAO+/AmoUr8prKTn030AQ3mQy3XymJ8WS8OxL5hTOEHWqdR8AAAKoUlEQVRevrz564RN080DGNdkWVJYoCgPU/n8zOfYMFSYrumMWAErUBQF6gJDR48ezQbAW2+99X3Sy/rD9fQH3AhwBEapdUjXCdcs7jS+fu43gqE8FF2fGovr169Hpz7HASQACLLiCIYYvIEZoALwkBWE64RpBwAUJ2tsgAg2QUErGAIuBBupK8BKp6oUZ+qmFiXCk1+uq7xpmbmeThGqrEqX/OfPkb7KJ3+4qX5pfuazbxjqZ2902lbAChRSAcHQxZVfD/arsLFgWD8ARoOKzqUu1wAk4IZ9wIefzrOvOLAC6ZosSNmJd/8Qh86Th6JoOfnYZ2amyQRBeZfps6mN98f0hXMd/TaZBnvBDm66aeDHX3qe/UYDfWpZUtzUlYAIl2O2fHgWZ6fWF01NKbyuzQZESlP5Jixgp7RS2EqtPymkKX+pq+kywRPlAJbkJ01Dac3XNQylvdb7VsAKWIGIuPbm7hj5yr9rOVjmB88iH2MJ4acpsLzVJ614DTapm7f0pDAkaEr95/eBq9msMUXWbnTxH8TEwFdnBvf5DrgKJ3gQ6OS1mu1YcaSuLDiEA4xSYEjTAC7ScPnpLWAD/0ofv4CMgIjzAizFA6jIP/GpbIInrQHCD+cENoRXPhU/x8ASaeAq783cVtN3ymM7rmEovQN43wpYASvwrgIAUVGsGJ3IRzPLUCMoYuCSNUjwBPxoGgyJGk2TCZAUp8Lq2Jahd771JWBgkE+nkjToy8KCP52Tmx/YU6sL/rkuAAF+2CcsdZpeF4gIZAQ58st5pTUbEBFOceAPQBHc4KaWJqxQihMXiKOsqR6cb2UxIj3ymca10H3DkG/9VsAKWIGaKpC39kgGrDga4ORyLX8eOEp/AiSdEwzpuEjubFYqPV3W6TVDGrDTwR8LSH66J72uMI1cQY/qCBiRP66xcSzAEQzNBjfyS5yKCzcFFCBG1wRuuDoH9ChPctPpMfmj3PjNlzdNi/ykm9LjnOLphGsYKlLvdF6sgBWwAgVRIJ36wuKjX3peFh+uCXxkUeJcHo4URxHcRjAkCNJ7hzr9NJkGbQ3+AoX8wK7r+fMKj5sHoUawIf+KD2uQzgEhgEUKUFwjTeVLfuViBUpBKLUKCejIVxqH4iLt/LSWYE35U3lTGFLacvN+dX6hrmGoCL3SebACVsAKlFgBPX0maEotSOwX8ZfCUB6ClN9ewBBTSfnpo1YDPlCRTj+la4EAFMAEoGBjX9NWgo3ZwCEFmdn8ATKy0hA/eSKs0hIE5Y8pG3lKwShf3hSGuJZuiq+dssyW//w1w5BavV0rYAWsgBWojQLAUDMIkgjdgiEN6Azyso6kg3MeDtJr+SkurQuSnxRmBCRygQz5a+am4Zv54Xy6aDu//oj0yBd5pXypX+UFaFP8+fKmMCT/edcwpFb6jnvT+w99ZAWsgBWwAlagtQIs5tZ0WDPf3YKh/HSToEBuHg50Xq6mp4CMPEw1Agniy1ufFFfebReGSBfgkVVK4bAWpaCj+LEEkV9AkPzoPG6+vGkZ2E830gOMDEPvb7WGoffr4SMrYAWsgBXokALdgqEUBBrtY1EBANKppLy/2a7l/c7lmHgFH63CAUTpmqN0f7aw+bzny0u8zfKQ9ztbOnO55mmyDnUaR2MFrIAVsALVUqBfMDSXQdx+33ldwUJ1MAxVq++6NFbAClgBK9AhBQxDnQGNhYJKL8IbhjrUaRyNFbACVsAKVEsBw5Bh6PTp0zE2NhbT09Nx7dq1oE3cuHGjcA3da4YKVyXOkBWwAlagGgoYhgxDhqFq9GWXwgpYAStgBeapgGHIMGQYmmfncTArYAWsgBWohgKGIcOQYagafdmlsAJWwApYgXkqYBgyDBmG5tl5HMwKWAErYAWqoYBhyDBkGKpGX3YprIAVsAJWYJ4KGIYMQ4aheXYeB7MCVsAKWIFqKGAYMgwZhqrRl10KK2AFrIAVmKcChiHDkGFonp3HwayAFbACVqAaChiG6gVDy5YtizVr1sTmzZtj165dcfjw4TAMVaMvuxRWwApYASswTwUMQ/WFod27dxuG5tlvHMwKWAErYAUqpIBhqD4wNPTwbYFlaHBwMLMMGYYq1JFdFCtgBayAFZi/AoKhy5cvx8Sau6IXHwx1Gv0BsKFHbo+BgYFYu3ZtbN26Nfbs2RNHjhyJM2fOxPj4uL9NNv9u5JBWwApYAStQZgUMQ/0Bk34AITC0YsWKWL9+fWzbti1ee+21OHr0qGGozB3YebcCVsAKWIGFK5DC0PjgPTG+elGMrrozzg/cEcNLvxann/hynHjsi3H80c/Hm0s+FwyoTLd4K5EGj9webz5yexx48B+yxdMbN26MHTt2xL59+2JoaCjOnj0bExMTcenSJX+1fuFdyjFYAStgBaxA2RS4ceNGXL9+Pa5cuRIXL16MkZGROHnyZBw6dChYU4IF4dlnn42nn346Vq5cGcuXL8/WnSxdujS8lUMD1glRd6tXr44NGzbEli1b4pVXXokDBw7E8ePH49y5czE5OZnBEG0BQKZdFO13U9Ey5PxYAStgBaxANRRg0GPwu3r1akxNTcWFCxeyaRMsBvv374+dO3dmQLRp06ZsIF23bl22AJfHs70VXwMWS7NGiKkxoBYQeumll2Lv3r3ZeqFTp05lAAwIs27MMFSNfu1SWAErYAWswBwUSGGIaRKmS86fP59Zh1hcy1QK76NhWuWFF17IFt4yoLLxrhpvxdaAemKx9Pbt2+PFF1/MLEKA0BtvvBFvvfVWNkU2NjaWLZ7GOiirkC1Dc+hE9moFrIAVsALlVkAwdO3atWyqTNYh1pGcOHEiW2B78ODBeP3117MFt0ydsQFI3sqhAfXFYmnqkKkxXrTI9Njw8HCMjo5mU2RYhWgDgqEitmpPkxWxVpwnK2AFrEAFFACG2JgeYaoM6xDrR5guw0LE24mBIqbNjh07lk2tYDFiQPVWDg2oL54aow6xBjE1BuwCQlgCp6ens7qnDag9FLFpG4aKWCvOkxWwAlagIgrIOpQCEWtIePcMA+bbb7+dLbLFksA7abyVTwPqDgACcFkkz9SYFk0zPVbktULqZoYhKWHXClgBK2AFuqJAHoiYNsFiABRhPQCMGEDZsBp5K5cG1Bt1SF0CQUyHYgUEhNLpMdpBUX+GoaLWjPNlBayAFaiIApoeYc0IG5YCBkmmzhgwgSMGT2/l1YA6ZKM+qVfqN7UIFRmE6GaGoYrcbFwMK2AFrECRFWgERIIigRGDqLdyakAdahMEacF00UGIfmMYKvLdw3mzAlbAClRMAUGRXFmL7L5jNSu7DqpXuWVpvoahstSU82kFrIAVqJACGiztvvPEXdV0KFtTNQyVrcacXytgBayAFbACVqCjChiGOiqnI7MCVsAKWAErYAXKpoBhqGw15vxaAStgBayAFbACHVXAMNRROR2ZFbACVsAKWAErUDYFDENlqzHn1wpYAStgBayAFeioAoahjsrpyKyAFbACVsAKWIGyKWAYKluNOb9WwApYAStgBaxARxUwDHVUTkdmBayAFbACVsAKlE0Bw1DZasz5tQJWwApYAStgBTqqgGGoo3I6MitgBayAFbACVqBsChiGylZjzq8VsAJWwApYASvQUQX+fym3xT/w0SvHAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image-3.png](attachment:image-3.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#请在此输入答案并运行#\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "请输入成绩55\n",
      "同学，你此次的分数为 55 分，等级为 不及格\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "#使用input要求用户输入成绩，使用int()转换数据类型为整数，用于与下一步数值的比较运算（是否大于等于90）\n",
    "score = int(input('请输入成绩'))\n",
    "level = ''\n",
    "\n",
    "if score >= 90:\n",
    "    level = '优秀'\n",
    "elif score >= 80:\n",
    "    level = '良好'\n",
    "elif score >= 60:\n",
    "    level = '及格'\n",
    "else:\n",
    "    level = '不及格'\n",
    "    \n",
    "print('同学，你此次的分数为' , score  , '分，等级为' , level)\n",
    "\n",
    "# 1. ,\n",
    "# 2. % 格式化字符串\n",
    "# 3. .format()\n",
    "# 4. f-string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#多层条件判断需要用到elif语句"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#A64646 size=2> **同学真棒，再接再厉。**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#A64646 size=2> **同学们有没有觉得题目很实用呢，下面的内容更加有趣呦！**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.【基础题】循环语句\n",
    "\n",
    "\n",
    "某文件记录了某超市若干商品的交易数据，其格式如下：\n",
    "\n",
    "| 商品代码 | 商品单价 | 交易数量 |\n",
    "|----------|----------|---------|\n",
    "| CZ0001  |   2000  |   3    |\n",
    "| CZ0002  |   4000 |    20   |\n",
    "| CZ0003  |   200  |    80   |\n",
    "| CZ0004  |   1000 |    15   |\n",
    "| CZ0005  |   10  |   2000   |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（1）请将该表格在Pyhton环境中输出，设定列表名称为：sale_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#请在此输入答案并运行#\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('CZ0001', 2000, 3), ('CZ0002', 4000, 20), ('CZ0003', 200, 80), ('CZ0004', 1000, 15), ('CZ0005', 10, 2000)]\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "sale_data = [\n",
    "    ('CZ0001', 2000, 3),\n",
    "    ('CZ0002', 4000, 20),\n",
    "    ('CZ0003', 200, 80),\n",
    "    ('CZ0004', 1000, 15),\n",
    "    ('CZ0005', 10, 2000)\n",
    "]\n",
    "print(sale_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（2）计算出各类商品当日的销售总价，并找出当日总收入最高的商品代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#请在此输入答案并运行#\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CZ0001 6000\n",
      "CZ0002 80000\n",
      "CZ0003 16000\n",
      "CZ0004 15000\n",
      "CZ0005 20000\n",
      "当日总收入最高的商品: CZ0002 总价: 80000\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "max_price = 0\n",
    "max_item = ''\n",
    "\n",
    "for name, price, num in sale_data:\n",
    "    total = price * num\n",
    "    print(name, total)\n",
    "    if total >= max_price:\n",
    "        max_price = total\n",
    "        max_item = name\n",
    "        \n",
    "print('当日总收入最高的商品:', max_item, '总价:', max_price)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#A64646 size=2> **“同学真棒，再接再厉，下面来看看思考题吧！”**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.【思考题】分支语句"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "社区举行一场体检活动，想要计算居民的健康程度，为此需要让系统在输入一个人的身高(m)和体重(kg)时，可以自动算出BMI指数(体重/身高的平方)，并判断BMI等级。其中BMI等级判断标准为：\n",
    "<br>BMI<18：过轻\n",
    "<br>BMI 18(含)-23.9(不含)：要求输入年龄，如果年龄≤60岁，则为标准；若年龄>60岁，则为过轻\n",
    "<br>BMI 23.9(含)-27.9(不含)：要求输入年龄，如果年龄≤60岁，则为超重；若年龄>60岁，则为良好\n",
    "<br>BMI 27.9(含)-32(不含)：肥胖\n",
    "<br>BMI≥32：严重肥胖\n",
    "\n",
    "\n",
    "注1：这里要用到嵌套条件函数的概念哦~同学可以思考如果在if里再用一次if会如何呢？\n",
    "<br>\n",
    "注2：大家要看清变量的取值区间，思考一下进行数值的大小比较时是否需要加等号呢？"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（1）计算出一个人的BMI指数。\n",
    "<br>提示：身高和体重中包含小数，而input()函数中输入的都是字符串类型，大家需要进行转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 请在此输入答案并运行\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "输入身高1.7\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "#使用input要求用户输入身高，使用float()转换数据类型为浮点数\n",
    "hight = float(input('输入身高'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "输入体重70\n"
     ]
    }
   ],
   "source": [
    "#使用input要求用户输入体重，使用float()转换数据类型为浮点数\n",
    "weight = float(input('输入体重'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24.221453287197235\n"
     ]
    }
   ],
   "source": [
    "#根据计算标准算出BMI指数(体重/身高的平方)，注意平方的表示是**呦\n",
    "bmi = weight / (hight ** 2)\n",
    "print(bmi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（2）算出BMI指数后，如果属于18-23.9或24-27.9的情况，则要求输入年龄，再给出判断结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 请在此输入答案并运行\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "请输入年龄21\n",
      "超重\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "#在条件嵌套函数中，BMI落在18-23.9以及24-27.9的区间时，还有年龄的条件判断，需要再嵌入新一层的if函数\n",
    "#因此我们需要再次使用input要求用户输入年龄，使用int()转换数据类型为整数，用于与下一步数值的比较运算（年龄是否大于60）\n",
    "#而当BMI落在其它区间时，无年龄的条件判断，此时就无须再嵌入新一层的if，可直接判断输出结果\n",
    "\n",
    "if bmi < 18:\n",
    "    print('过轻')\n",
    "elif bmi < 23.9:\n",
    "    age = int(input('请输入年龄'))\n",
    "    if age <= 60:\n",
    "        print('标准')\n",
    "    else:\n",
    "        print('过轻')\n",
    "elif bmi < 27.9:\n",
    "    age = int(input('请输入年龄'))\n",
    "    if age <= 60:\n",
    "        print('超重')\n",
    "    else:\n",
    "        print('良好')\n",
    "elif bmi < 32:\n",
    "    print('肥胖')\n",
    "else:\n",
    "    print('严重肥胖')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#A64646 size=2> **同学们有没有学会这么实用的嵌套函数呢？同学们平时记得多多练习呦！大家也可以对照BMI标准给家人朋友也测试一下呢！**</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#A64646 size=2> **继续加油喔，快和小伙伴一起开启明天的课程学习吧！**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.【思考题】循环语句"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在列表data中记录了某学校不同班级各个学生的数学考试成绩\n",
    "\n",
    "``` python\n",
    "data = [\n",
    "    ('A班', [4, 75, 82, 29, 31, 30, 6, 66, 60, 99]),\n",
    "    ('B班', [72, 2, 7, 75, 58, 95, 10, 41, 34]),\n",
    "    ('C班', [30, 37, 51, 26, 64, 6, 93, 13, 49, 72, 7, 93, 27, 64, 74, 58, 38, 33, 56, 54]),\n",
    "    ('D班', [37, 72, 91, 17, 6, 70, 77, 10, 86, 1, 41, 53, 24, 37, 78, 66, 88, 99]),\n",
    "    ('E班', [5, 61, 79, 95, 56, 41, 31, 71, 38, 61, 14, 55, 41, 93, 30, 93]),\n",
    "    ('F班'，[3, 47, 29, 41, 69, 66, 24, 43, 62, 44, 82, 99])\n",
    "]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "请将data列表在Pyhton环境中输出，计算各个班级的平均成绩，并找出平均成绩最高的班级"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#请在此输入答案并运行\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A班 48.2\n",
      "B班 43.77777777777778\n",
      "C班 47.25\n",
      "D班 52.94444444444444\n",
      "E班 54.0\n",
      "F班 50.75\n",
      "平均分最高的班级是: E班 平均成绩是: 54.0\n"
     ]
    }
   ],
   "source": [
    "#参考答案#\n",
    "\n",
    "data = [\n",
    "    ('A班', [4, 75, 82, 29, 31, 30, 6, 66, 60, 99]),\n",
    "    ('B班', [72, 2, 7, 75, 58, 95, 10, 41, 34]),\n",
    "    ('C班', [30, 37, 51, 26, 64, 6, 93, 13, 49, 72, 7, 93, 27, 64, 74, 58, 38, 33, 56, 54]),\n",
    "    ('D班', [37, 72, 91, 17, 6, 70, 77, 10, 86, 1, 41, 53, 24, 37, 78, 66, 88, 99]),\n",
    "    ('E班', [5, 61, 79, 95, 56, 41, 31, 71, 38, 61, 14, 55, 41, 93, 30, 93]),\n",
    "    ('F班', [3, 47, 29, 41, 69, 66, 24, 43, 62, 44, 82, 99])\n",
    "]\n",
    "\n",
    "max_avg_score = 0\n",
    "max_klass_name = ''\n",
    "\n",
    "for klass_name, score_list in data:\n",
    "    total_score = sum(score_list)\n",
    "    count = len(score_list)\n",
    "    avg_score = total_score / count\n",
    "    print(klass_name, avg_score)\n",
    "    if avg_score >= max_avg_score:\n",
    "        max_avg_score = avg_score\n",
    "        max_klass_name = klass_name\n",
    "        \n",
    "print('平均分最高的班级是:', max_klass_name, '平均成绩是:', max_avg_score)\n"
   ]
  }
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